Prediction of Clearance

Predicting Drug Clearance Using the Simcyp Simulator

The Simcyp® Simulator predicts in vivo drug clearance from in vitro data, for the average individual and across populations.

It also measures variability in clearance as a function of:

Proportional metabolism by each enzyme

Genetic/environmental variations in enzyme abundance

Ethnic differences in genotype frequencies and levels of CYP and UGT enzymes

Physiological differences (eg, liver size and hepatic blood flow)

Changes in physiology and enzymology with age

Pediatric populations

The Simcyp Pediatric Simulator models pharmacokinetic behavior in infants, neonates and children. This facilitates first-time dosing decisions and the design of clinical studies.

The Simcyp Simulator includes a full physiologically-based pharmacokinetic (PBPK) model and extensive libraries on demographics, developmental physiology and the ontogeny of drug elimination pathways. It can simulate population variability in pharmacokinetics in any age range and quantify potential drug-drug interactions. Retrograde modeling allows predictions to be made from either in vitro data or adult in vivo data.

Prediction of ethnic differences in clearance

By including comprehensive population-specific data, the Simcyp Simulator predicts drug clearance in different ethnic groups.

Most clinical trials in Europe and the USA are performed in Caucasians, while those in Japan are almost exclusively in Japanese subjects.

Inter-ethnic differences in drug disposition may be due to differences in genetic, physiological, demographic and environmental factors. Simcyp Simulator databases contain such information, allowing simulation of outcomes in different virtual populations and assessment of the impact of ethnicity. For example, specific information on demography, physiology and enzyme abundances in Japanese has been collated within the Simcyp Simulator, allowing comparisons of drug disposition against Caucasian populations.

Disease populations

The population libraries within the Simcyp Simulator include information on the demographics of various disease groups and the associated physiology and enzymology differences. This allows pharmacokinetic behavior to be predicted in representative virtual patient populations, rather than an ‘average’ healthy male subject. For example, simulations can be performed in virtual populations of patients with liver cirrhosis (mild, moderate or severe) or renal impairment (moderate or severe). The effects of obesity and morbid obesity on pharmacokinetic behavior can also be simulated.

In addition, a typical population of healthy subjects is also defined within the Simcyp Simulator, allowing virtual ‘Phase I’ pharmacokinetic studies to be simulated.

Pharmacogenetics

The Simcyp Simulator can assess the impact of genetic polymorphisms in drug metabolizing enzymes and transporters on the pharmacokinetics of new chemical entities. Its databases contain genetic information on different populations. Phenotype frequencies, derived from comprehensive meta-analyses, are used to simulate populations with representative numbers of poor metabolizers (PMs) with respect to polymorphic CYPs (eg, CYP2D6).